Home The Growth Contribution of China’s Regional Coordinated Development Strategy—On the Dispute of Regional Policy Paths
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The Growth Contribution of China’s Regional Coordinated Development Strategy—On the Dispute of Regional Policy Paths

  • Meng Nian , Haipeng Zhang and Yao Wang
Published/Copyright: December 30, 2024

Abstract

Balancing macroeconomic growth with regional equilibrium development is essential for China’s pursuit of the modernization through regional coordinated development. Taking a macroeconomic output perspective and employing a counterfactual framework, this paper evaluates the economic growth effects of China’s “place-based” and “people-based” regional policies, and explores the future implementation effects and optimal combinations of these policies under different market environments. Given that “people-based” policy cannot address market failures in spatial dimensions, the essence of the academic debate over regional policy paths lies in different understandings of the relationship between government and markets.

1 Introduction

In order to find the best balance between narrowing the regional development gap and promoting macroeconomic growth, China experienced the practice of regional development strategy from balanced development to unbalanced development and then to coordinated development. In particular, since the strategy of coordinated regional development is proposed, along with the successive implementation of the strategies of developing the western region, revitalizing the old industrial base in Northeast China, and rising in the central region, China’s economic layout gradually change from the previous concentration of various factors and industrial activities to the southeast coastal region (Wei, 2008), and gradually change from the southeast coastal area to the central and western regions and the northeast region, and coordinated development become a new idea and new task in China’s regional development practice. When regional development strategies for the central and western regions and the northeast are proposed, some scholars are worried about whether economic growth would behindered by resource misallocation and overall efficiency loss. From practical point of view, the implementation of these strategies does not change the trend of long-term stable growth of China’s economy, but deepens regional coordination and coordinated development. Since the 18th National Congress of the Communist Party of China, in order to solve the problem of unbalanced and inadequate development, China adheres to the concept of coordinated development and thoroughly implements the strategy of coordinated regional development, which has further enhanced the coordination, balance and linkage of regional development.

As an important starting point for embodying regional development ideas and implementing regional development strategies, the implementation of regional policies not only has far-reaching economic and social impacts, but also often requires a large amount of financial support. From the perspective of specific implementation targets and goals, regional policies can be roughly divided into two categories: “place-based” and “people-based”. The “place-based” policy focuses on “regions” and mainly relies on the power of the government, focusing on narrowing regional disparities by improving the development conditions of underdeveloped areas (such as implementing tax incentives and improving the level of infrastructure such as transportation).[1] The “people-based” policy takes “people” as the target of policy, mainly relies on market forces, and focuses on promoting the transfer of population from underdeveloped areas to developed areas by eliminating barriers to population mobility and reducing the cost of population movement, so as to achieve the equality of labors’ income or welfare level (Neumark and Simpson, 2015; Duranton and Venables, 2018).

Through years of research, some scholars recognize that it may not be possible to fully assess the effectiveness of regional policies using traditional methods of economic analysis. The externalities brought about by the regional policy itself, coupled with the difficulty of implementing regional policies and the environmental differences faced by countries or regions of different sizes, increase the difficulty of estimating the effectiveness of regional policies, which also leads to great controversy in the academic community about the path and effect of regional policies.

2 Literature Review of Existing Regional Policies Research

There has been a long-standing debate in academia about whether governments should aim for “regional prosperity” (that is, “place-based”) or “people’s prosperity” (that is, “people-based”) when formulating and implementing regional policies.

Typically, “place-based” policies can improve the development conditions of less developed regions, attract foreign investment and increase employment, and achieve regional prosperity through the implementation of the following measures. First, large-scale infrastructure construction should be carried out. For example, by strengthening the construction of transportation infrastructure, improving the market accessibility between backward and developed regions (Haines and Margo, 2006; Duranton and Turner, 2012; Nian, 2019), and making up for the lack of energy and telecommunications infrastructure supply in backward areas, is the basis for ensuring the economic development of the region.[1] Second, regional preferential tax policies should be implemented. In the early days of China’s strategy for the large-scale development of the western region, the enterprise income tax levied at the rate of 15 percent in the region, attracting a large amount of investment from foreign enterprises (Luo et al., 2019). Third, other inclined policies should be implemented. For example, government set relatively loose entry thresholds for economic development zones and industrial parks in backward areas, provide subsidies to enterprises and high-skilled talents who move into backward areas (Duranton and Puga, 2004), promote the formation of new specialized industrial clusters and raise the level of knowledge and technology spillover, and adopt appropriate taxation in developed areas to subsidize underdeveloped areas (Fajgelbaum and Gaubert, 2020).

While numerous studies show that government’s policies to promote economic development in a particular region can help increase the welfare of the target region, there are still many studies that question the effectiveness of “place-based” policies. First, “place-based” policies are a “zero-sum game”. Some scholars believe that such policies only transfer economic activities spatially, and that the benefits enjoyed by the target region are at the expense of other regions (Roback,1982). Second, the “place-based” policy is ineffective in a long time. Some scholars cite the Appalachian highway system in the United States as an example, arguing that the project improved the local economy in the 70s of the 19th century, but did not lead to long-term development (Glaeser and Gottlieb, 2008). Third, the cost of “place-based” policies is too high. Some scholars point out that although the Empowerment Zones project promoted by the U.S. government increase employment levels in backward areas, the government spending on creating a job is as high as $100,000 (Busso and Kline,2008). Fourth, “place-based” policies lead to “ecological fallacy”. Some scholars believe that policymakers often ignore individual differences in the policy-making process and only target the average characteristics of individuals in the region, resulting in most of the aid actually being used for the relatively wealthy groups, while the unemployed or poor groups who are really in need do not benefit from it (Edel, 1981).

The “people-based” policy is based on the promotion of the free movement of labor. A number of studies confirm that facilitating the migration of labors from backward regions with lower productivity to developed regions with higher productivity can not only increase country’s total economic output, but also help narrow regional disparities (Bryan and Morten, 2019). As a result, some scholars believe that “people-based” policies are more effective. Promoting the migration of population to developed areas can not only solve the employment problems and poverty problems in underdeveloped areas, but also promote the agglomeration economy of developed regions. With the continuous improvement of regional productivity, economic activities in developed regions began to spread to less developed regions, and finally achieve balanced regional development.

However, “people-based” policies rely heavily on the full effectiveness of an ideal market. In reality, there are at least three spatial dimensions of market failure, which form strong constraint on the effectiveness of this policy. First, the friction of labor flow cannot be completely eliminated. The physical cost of labor migration cannot be exactly zero. In reality, there are other forms of friction, such as differences in culture, language, skills and habits (Hellerstein et al., 2011). Housing prices in developed areas will continue to rise as the number of immigrants increases, and the skills and occupational barriers for the labor required in the region will also continue to increase (Johnson and Kleiner, 2020). Second, there may be a margin of ineffectiveness in developed regions. When factors such as high-skilled labor and high-quality capital are highly concentrated in developed regions, the marginal returns brought by new high-end factors gradually decline, and even the marginal returns tend to be 0 or negative due to excessive aggregation, resulting in the phenomenon of inefficient margin. This can be thought of as a result of factor space mismatch. Third, there is spatial boundary for the diffusion effect. Agglomeration economic theory can only explain how the economic activity of the central city spreads to the peripheral secondary cities or satellite cities. Even if the diffusion effect occurs, it is difficult for economic activity to move to remote, less developed areas. It can be seen that the market failure in the spatial dimension leads to the failure of the “people-based” policy to meet the theoretical expectations. The massive outflow of high-skilled talents and young labor force from underdeveloped regions lead to an imbalance in the population structure and deterioration of economic development conditions in these regions, while the advantageous resources in developed regions are continuously concentrated, and regional development show “Matthew effect”. More seriously, the continued recession of the region can lead to lack of resources for public services and even political instability (Moretti, 2014; Austin et al., 2018).

3 Model Construction Based on Macro Aggregate Output

This paper intends to establish a macroeconomic model with micro basis, and incorporate individual heterogeneity into the analytical framework, so as to estimate the impact of the two types of policy paths on macro aggregate output (Bryan and Morten, 2019).

3.1 Model Settings

Assuming that an economy is composed of N different regions, and there are differences in the basic conditions for development (R) among the regions, labors decide whether to migrate by comprehensively considering the difference in wage income, the difference in basic conditions for development, and the cost of migration between the place of birth o and the migration destination d . The “people-based” policy uses “migration cost” as proxy variable and has an impact on the region and macroeconomy by reducing the cost of labor migration and promoting the free movement of labor. The “place-based” policy takes “basic conditions for regional development” as proxy variable, which affects the decision-making or direction of labor migration by improving the basic conditions for development in backward areas and narrowing the differences in basic conditions for development among regions, and then has an impact on regional or overall economic growth.

The wages wido of labor i depends on the individual’s skills, productivity at the place of work, and the level of education at the place of birth, that is:

wido=ϵidadeoμdow (1)

Among them, ϵid indicates the skill level of the labor, which is related to the place of work d. ad is the labor productivity at place of work d. eo is the level of education of the labor, which is related to the place of birth of the labor o. μdow is the perturbation term that affects the wages of the labor and obeys lognormal distribution with mean of 1. In general, regions with better development conditions have better public services such as medical care, education and sanitation, more convenient leisure, entertainment and shopping, and relatively good social and legal environment, which is equivalent to an increase in the income level of workers in the region. For labors, there are migration costs, on the one hand, economic costs, such as rent, house purchases, and travel to and from their hometowns, and on the other hand, hidden costs, such as personal connections. Taking into account the above factors, the actual budget constraints are as follows:

ωido=widoRd1τdoμdoω (2)

Among them, the definition Rd represents the development conditions of region d, and τdo represents the cost of migration between place of birth o and place of work d, τdo ∈ [0,1]. μdow is the perturbation term that affects the income of the labor, and it also obeys a lognormal distribution with a mean of 1.

The consumption function of labor adopts the form of constant substitution elasticity (CES), which depends on the consumption of differentiated products, and the indirect utility function is obtained by solving the utility maximization problem:

Uido=ϵidadeoμdowRd1τdoμdoω=Ωdoϵideo (3)

Labors choose to work in regions where utility is maximized, and the distribution of skills is based on the Fréchet equation. Labor i chooses to work in Region d, then Ωdo ϵid > Ωeoϵie, ∀ed. According to the distribution function of workers’ skills, the proportion of individuals born in o who choose to migrate to d in the total population of o region is obtained:

pdo=Prϵie<ΩdoΩeoϵid=Ωdoθe=1NΩeoθ=adRd1τdoμdowμdoωθe=1NaeRe1τeoμeowμeoωθ (4)

Among them, θ represents regional skill heterogeneity.

According to the nature of the Fréchet distribution function, the average skill level of the labors working in the region d is E[ϵid] = pdo –1/θΓ, among them ΓΓ(1 – (θ(1 – ρ))–1), Γ(·) is gamma function. According to Equation (1), the average wage of labor is:

w¯do=pdo1θΓ¯adeoμdow (5)

Finally, the output level is calculated. The regional production function adopts the Cobb-Douglas form:

yd=AdL~dαKdβ (6)

Among them, Ad denotes total factor productivity, Kd denotes capital stock, and d denotes effective labor. α is the elasticity coefficient of labor output, and β is the elasticity coefficient of capital output, α + β = 1. According to existing research, productivity is related to labor agglomeration, so in this paper, total factor productivity is set as: Ad = dγ. Total factor productivity (TFP) depends on the average skill level ϵdo of region d and the degree of agglomeration γ. Effective labor d depends on the skills and education level of region d, that is:

L~d=o=1NLdopdo1θΓ¯eo (7)

Among them, Ldo indicates the number of labors who have migrated from o to d. In this case, the output function of region D is:

yd=o=1NLdoadRd1τdoμdowμdoωθe=1NaeRe1τeoμeowμeoωθ1θΓ¯eoα+γKdβ (8)

The level of GDP Y, which depends on the output of products in each region, is expressed as constant substitution elasticity (CES) production function, that is:

Y=d=1No=1NLdoadRd1τdoμdowμdoωθe=1NaeRe1τ e oμeowμeoωθ1θΓ¯eoα+γKdβσp1σpσpσp1 (9)

3.2 Parameter Identification

First, the logarithmic transformation of Equation (4) and Equation (5), then:

lnpdo=θlnad+θlnRd+θln1τdolne=1NΩeoθ+θlnμdow+lnμdoω (10)
lnw¯do=lnΓ¯+lnad+lneo1θlnpdo+θlnμdow (11)

Equations (10) and (11) involve two types of parameters: one is endogenous parameters, {θ,eo,ρ,ad,τdo,Rd}. The second is exogenous parameters, {pdo, wdo, σp, γ}.

In order to be able to identify the model, some parameters are assumed or standardized here. First, regarding the migration cost τdo, it is assumed that there is no migration cost within the region and that the migration cost is independent of the direction, then τdd = 0, τdo = τod. Second, set region s as the benchmark area, and standardize the education level and development basic conditions of the region to 1, then es = 1, Rs = 1. In this paper, the base city is set to be Beijing.

3.2.1 Endogenous Parameter Identification

First, skill heterogeneity θ and education level eo at the place of birth.

Equation (11) can be separated into two parts: the fixed effect of destination and the fixed effect of birth place. The destination fixed effect consists of labor productivity and skill parameters, then DestinationFEd^ = ln Γ + ln ad. The fixed effect of the place of birth is the level of education in the place of birth, then OrigionFEo^ = lneo. The average wage is regressed on the proportion of the migrant population pdo to control the fixed effect of place of birth and destination:

lnw¯do=DestinationFEd+βlnpdo+OrigionFEo+μdow (12)

The endogenous parameters can be calculated as θ=1β,eo=exp(OrigionFEo^).

Second, the correlation of skills ρ and labor productivity at place of work ad. Take advantage of the nature of the Fréchet distribution, then:

Varwidow¯do2=Γ12θ(1ρ)Γ¯21 (13)

In the above equation, the variance Var[wido] and the mean wdo of labor wages and the skill heterogeneity θ are known, and the skill correlation parameter ρ is obtained by solving the equation. Combining with the skill heterogeneity parameter θ, we can obtain the value of Γ, which is substituted in the fixed effect of the destination, then the labor productivity level is obtained ad = exp ( DestinationFEd^ – lnΓ).

Third, the migration cost is τdo.

Solving Equation (10) obtains the estimation equation for the migration cost τdo as:

τdo=1explnpdolnpoo+lnpodlnpdd2θ (14)

Fourth, the conditions for the development of the working region Rd.

Equation (10) is differentiated, which can eliminate ln(e=1NΩeoθ) to obtain relative regional development conditions:

lnRdRs=o=1Nlnpdoo=1NlnpsoNθlnadaso=1Nln1τdoo=1Nln1τsoN (15)

By substituting the proportion of migrant labor pdo the migration cost τdo and the skill heterogeneity parameter θ into Equation (15), we can obtain the estimated value of the gap in the basic conditions of regional development RdRs .

3.2.2 Exogenous Parameters

In order to obtain the income and size of the migrant labor force, this paper uses census data of China and matches it with the help of micro-survey data. The census data of China provides information about the individual’s place of birth and place of work, covering all regions of the pairing and the sample size is large enough. However, census data does not include individual income information, and needs to be matched using micro-survey data such as China Family Panel Studies (CFPS) and China Migrants Dynamic Survey (CMDS).

Regarding the proportion of migrant labor force pdo, the labor force between the ages of 16 and 55 in the census data is selected for calculation, and the samples of the working-age labor force who are not in the labor market[1], as well as those who live in Hong Kong of China, Macao of China, Taiwan province of China or other countries at the time of the census, whose household registration is pending, and whose place of birth is not in China, are deleted.

About the average wage of labors wdo. By combining the two micro-survey databases of CFPS and CMDS[2] to calculate the wage level of labors by year, and the wage level of labors in 2000 is indirectly estimated by calculating the elasticity coefficient of years of education and labors’ income[3].

About the product substitution elasticity σp. According to scholars’ estimates, the substitution elasticity of China’s products is 2.82 from 1991 to 1995, 3.17 from 1996 to 2000, and 3.5 from 2001 to 2006 (Zhao and Cai, 2009). Based on the existing research, this paper sets the benchmark value of China’s product substitution elasticity in 2000 to σp = 3, and estimates the 2010 and 2020 years on this basis, and uses different product substitution elasticity values to test the robustness and simulate the future trend of China’s regional policy.

About the Aggregation Index γ. Existing studies generally believe that the value of the agglomeration index is 0.01–0.02 in developed countries, 0.01–0.1 in developing countries, and close to 0.05 in East Asian countries (Bryan and Morten, 2019). In this paper, the benchmark value of the agglomeration index in 2000 is set to γ = 0.05, and the agglomeration index in 2010 and 2020 is estimated according to the method of non-farm employment population density estimation of China’s agglomeration index, and different agglomeration indices are used to test the robustness and simulate the future trend of China’s regional policies.

3.3 Counterfactual Model Setting

The core of the “place-based” policy is to improve the conditions for development in less developed regions, with the aim of narrowing the development gap between regions. It is assumed that the adjustment intensity of “place-based” policies is expressed by the coefficient κG, and Rd 1–κG represents the regional development conditions under government regulation, and κG ∈ [0,1]. κG = 0 is the actual state, and κG = 1 indicates the state of equal regional development conditions. κG reflects the degree of regulation of “place-based” policies, and the higher the value, the greater the degree of regulation. The core of the “people-based” policy is to promote free movement of labor, with the aim of reducing the cost of labor migration. It is assumed that the degree of regulation of the “people-based” policy is represented by the coefficient κτ, (1 – τdo)1–κτ represents the cost of labor migration under government regulation, and κτ ∈ [0,1]. κτ = 0 is the actual state, and κτ = 1 is the state without labor migration costs. κτ reflects the degree of regulation of “people-based” policies, and the higher the value, the greater the degree of regulation.

The total output at this point can be expressed as:

Yc=d=1No=1NLdoadRd1κG1τdo1κzμdowμdoωθe=1NaeRe1τeoμeowμeoωθ1θΓ¯oα+γKdβσp1σpσpσp1 (16)

According to the parameter identification strategy above, the relevant parameter values of the model can be obtained (see the Table 1 below).

Table 1

The List of Benchmark Model Parameters

Parameter Definition Estimation Equation Numeber 2000 year 2010 year 2020 year
Endogenous θ Skill heterogeneity Regression coefficients (12) 1 18.259 24.326 29.005
ρ Skill relevance Fréchet distributional nature (13) 1 0.841 0.880 0.898
Γ Technical parameters ΓΓ (1 – 1/θ(1 – ρ)) 1 2.594 2.594 2.641
ad Workplace productivity Dividing fixed effect by ln(Γ) (12) 31 3.611 4.110 7.493
eo Educational level of birth place Normalization, regression coefficients (12) 31 0.813 0.942 0.986
τdo Migration costs Migration influencing factors (14) 961 0.312 0.231 0.186
RdRs Gaps in the basic conditions for regional development Normalized, difference (15) 31 0.855 0.885 0.901

Exogenous wdo Average wage Microdata (Survey) S1 961 1612.66 2692.41 5009.425
pdo Population migration ratio d ≠ 0 Microdata (Census) S2 930 0.0023 0.0044 0.0049
d = 0 Microdata (Census) S2 31 0.932 0.868 0.852
σp Product substitution elasticity References 1 3 3.5 3.850
γ Aggregation index References 1 0.050 0.089 0.094
  1. Source: S1: 2010 and 2020 CFPS data; 2011 and 2017 CMDS data; S2: Chinese census data in 2000, 2010 and 2020.

4 Evaluation of the Effect of China’s Regional Coordinated Development Strategy from 2000 to 2020

4.1 Evaluation of the Effect of “Place-Based” Policies

The estimated results of model parameters show that the average gap between regional development conditions in China is 0.855 in 2000, 0.885 in 2010 and 0.901 in 2020, indicating that the regional development conditions are shrinking. The disparity in regional development conditions is relative indicator, and the closer the indicator to 1, the smaller the regional disparity. Assuming that the government does not implement the “people-based” policy, according to Rdt=(Rd0)1κG and Equation (16), from 2000 to 2010, the implementation of the “place-based” policy is κG = 0.223, which promotes the increase of total output by 9.577%. From 2010 to 2020, the implementation of the “place-based” policy is κG = 0.149, which promotes the increase of total output by 6.380%. From 2000 to 2020, the implementation of the “place-based” policy is κG = 0.338, which promotes the increase of total output by 16.568%.

At the same time, while keeping the cost of migration at 2010 levels, the aggregate output curve for the implementation of only “place-based” policies is estimated. The results are shown in Figure 1(a). There is an inverted U-shaped relationship between the implementation of “place-based” policies and aggregate output. When the degree of implementation of the “place-based” policy is κG = 0.547, the policy has the largest effect on the improvement of total output, reaching 22.988%, and then the effect of this policy on output begins to weaken slowly. As of 2020, the implementation of China’s “place-based” policy has not yet reached the optimal level, indicating that there is still room for further improvement of “place-based” policies under the existing conditions.

Figure 1 Changes in Policy Implementation and Aggregate Output in Different Regions
Figure 1

Changes in Policy Implementation and Aggregate Output in Different Regions

4.2 Evaluation of the Effect of “People-Based” Policies

The estimation results of model parameters show that the migration cost τdo is 0.312 in 2000, 0.231 in 2010 and 0.186 in 2020, and the inter-regional migration cost shows downward trend. Assuming that the government does not implement the “place-based” policy, according to 1τdot=(1τdo0)1κτ and Equation (16), the degree of implementation of the “people-based” policy is κτ = 0.298 from 2000 to 2010, which promotes the increase of total output by 13.245%. From 2010 to 2020, the degree of implementation of the “people-based” policy is κτ = 0.216, which promotes an increase the increase of total output by 7.559%. From 2000 to 2020, the degree of implementation of the “people-based” policy is κτ = 0.449, which promotes the increase of total output by 21.805%.

Similarly, while keeping the regional development base at 2010 levels, the aggregate output curve for the implementation of only “people-based” policies is estimated. The results are shown in Figure 1(b). There is an S-shaped relationship between the implementation of “people-based” policies and the total output, that is, the marginal output of “people-based” policies increases first and then decreases. In addition, we also find that as of 2020, the implementation of China’s “people-based” policies has not reached an optimal level, indicating that there is room for “peoplebased” policies to further improve under the existing conditions.

4.3 Evaluation of the Combined Effects of the Two Types of Policies

The combined effect of “place-based” and “people-based” policies contributed to the increase of total output by 29.405% between 2000 and 2020. The policy mix is more effective than implementing regional policy alone. In terms of impact on aggregate output, the output level of this policy mix is 12.837% higher than that of “place-based” policies alone, and 7.600% higher than that of “people-based” policies alone. From 2000 to 2020, China’s real GDP grew by 427.651%, and the share of the regional coordinated development strategy contributed 6.841% to the overall economic growth through the two types of regional policy paths: “people-based” and “placebased”.

According to the estimates, there may be mutually reinforcing effect between “place-based” and “people-based” policies, that is, whether “place-based” policies are more effective may depend on the effect of “people-based” policies in the same period, and vice versa. To this end, this paper further simulates the regional policy output curve.

Figure 2 (a) shows the impact of “place-based” policies on aggregate output, given different levels of “people-based” policy implementation. Specifically, under the condition of “people-based” policy implementation degree κτ = 0, when the “place-based” policy implementation degree is κG = 0.547, the total output increase the most, with the increase of 22.988% (as shown in point A). Under the condition of “people-based” policy implementation degree κτ = 0.298, when the “place-based” policy implementation degree is κG = 0.345, the total output increase the most, with the increase of 27.393% (as shown in point B).

Figure 2 Policy Implementation and Mutually Reinforcing Effects in Different Regions
Figure 2

Policy Implementation and Mutually Reinforcing Effects in Different Regions

Figure 2 (b) shows the impact of “people-based” policies on aggregate output under different levels of “place-based” policy implementation. Specifically, under the condition of the implementation degree of the “place-based” policy κG = 0, when the implementation degree of the “people-based” policy is κτ = 0.893, the total output increases the most, with the increase of 32.568% (as shown in point D). Under the condition of implementation degree of “place-based” policy κG = 0.223, when the “people-based” policy implementation degree κτ is close to 1, the total output increase the most, with the increase of 36.153% (as shown in point E). From the perspective of the simulated regional policy output curve, there is clear mutual promotion effect between “people-based” policy and “place-based” policy.

5 Simulation of Regional Policy Effects in China and Discussion on Optimal Combination

5.1 Short-Term: The Market Environment Remains Unchanged

The market environment usually does not change significantly in the short term, that is, the product substitution elasticity and aggregation index remain unchanged. Taking 2020 as the benchmark (that is, σ = 3.85 and γ = 0.094), the short-term impact of regional policies on aggregate output since 2020 is simulated by adjusting the parameters κG and κτ, and the optimal path for the implementation of China’s regional coordinated development strategy is discussed.

First, the impact of implementing only “place-based” policies on aggregate output is observed, with migration costs remaining unchanged at 2020 levels. This is shown in Figure 3(a). Although the implementation of “place-based” policies also presents an “inverted U-shaped” relationship with total output, it is obviously asymmetrical and “steep on the left and slow on the right”, indicating that the losses caused by insufficient implementation of “place-based” policies are greater than those caused by excessive implementation. When the implementation degree of “place-based” policy is κG = 0.266, it has the greatest effect on the total output, which can increase the total output by 23.237%.

Figure 3 Simulation of the Short-Term Effects of Policy Implementation in Different Regions
Figure 3

Simulation of the Short-Term Effects of Policy Implementation in Different Regions

Second, the impact of implementing only “people-based” policies on aggregate output is observed, while development conditions remain unchanged at 2020 levels. This is shown in Figure 3(b). The implementation of the “people-based” policy also presents “S-shaped” relationship with the total output, and the lower the migration cost, the greater the effect of the “people-based” policy on the total output. However, in reality, due to the market failure in the spatial dimension, the cost of labor migration cannot be reduced indefinitely. The United States is considered to be the country with the highest degree of labor freedom of migration, and its migration cost is τdoUS = 0.15 . When the cost of relocation in China is comparable to that of the United States, the implementation of the “people-based” policy at this time is κτ = 0.211, the increase of the total output only by 7.38%.

Finally, the optimal combination of the two types of policies in the short term is described. This is shown in Figure 3(c). The optimal regional policy mix route to maximize the total output is obviously biased towards the “place-based” policy, indicating that the short-term optimal regional policy mix route after 2020 should be mainly based on the “place-based” policy and supplemented by the “people-based” policy.

5.2 Long-Term: The Market Environment Changes

5.2.1 Changes in the Elasticity of Product Substitution

With the continuous improvement of the integration of China’s domestic market, the elasticity of product substitution will continue to increase. Based on the estimation of domestic and foreign scholars, this paper selects the product substitution elasticity values of 1.5, 3, 5, 7 and 10 for analysis. When discussing the impact of product substitution elasticity on regional policy utility, assuming that the aggregation index remains unchanged, the value of the 2020 benchmark model is γ = 0.094.

Firstly, assuming that the migration cost and agglomeration index remain unchanged, the impact of the implementation of “place-based” policies on total output under the substitution elasticity of different products is observed. This is shown in Figure 4(a). Under the condition of κτ = 0 and γ = 0.094, the impact curve of “place-based” policy on total output diverges with the change of product substitution elasticity. In general, the higher the elasticity of product substitution σ, the greater the effect of “place-based” policies on total output. The smaller the elasticity of product substitution σ, the smaller the effect of this policy on the improvement of total output. In view of the fact that the elasticity of product substitution is closely related to the degree of regional market integration, the greater the elasticity of product substitution, the higher the degree of regional market integration. The smaller the elasticity of product substitution, the more serious the market segmentation among regions. This suggests that “place-based” policies are not conducive to overall economic growth under conditions of high market fragmentation (namely, σ is small). This conclusion is in line with existing research that market segmentation is more conducive to local economic growth than to overall economic growth (Lu and Chen, 2009).

Figure 4 Regional Policy Implementation and Aggregate Output Changes under the Substitution Elasticity of Different Products
Figure 4

Regional Policy Implementation and Aggregate Output Changes under the Substitution Elasticity of Different Products

Secondly, assuming that the basic conditions of regional development and the agglomeration index remain unchanged, the impact of the implementation of “people-based” policies on the aggregate output under the substitution elasticity of different products is observed. This is shown in Figure 4(b). Under the condition of κG = 0 and γ = 0.094, the relationship curve between “people-based” policy and aggregate output is relatively stable under the influence of the substitution elasticity of different products, and only fluctuates slightly. In general, the greater the elasticity of product substitution σ, the greater the effect of the “people-based” policy on the improvement of total output, but the incremental impact is weaker than that of the “place-based” policy. This indicates that the change of product substitution elasticity has more obvious impact on the implementation effect of the “place-based” policy.

Finally, assuming that the agglomeration index remains unchanged, the impact of the implementation of “place-based” and “people-based” policies on aggregate output is observed under the substitution elasticity of different products. This is shown in Figure 4(c). Under the condition of keeping γ = 0.094 constant, with the change of the elasticity of product substitution, the relationship between the “place-based” and “people-based” policy combinations and the total output is relatively divergent, which is mainly caused by the large fluctuation of the curve relationship between the “place-based” policy and the aggregate output under different substitution elasticity of product. With the increase in the elasticity of product substitution, the increase in aggregate output is greater due to the combined effect of the policy mix.

5.2.2 Change of Aggregation Index

The agglomeration index γ reflects the degree of economies of scale, and the larger the γ, the higher the degree of economic agglomeration. According to the discussion of the aggregation index above, the values of γ ∈ [0.01,0.3] are selected for analysis. When discussing the impact of the change of agglomeration index on the utility of regional policies, assuming that the elasticity of product substitution remains unchanged, the value of the 2020 benchmark model is σ = 3.85.

Firstly, assuming that the migration cost and product substitution elasticity remain unchanged, the impact of the implementation of “place-based” policies on the aggregate output under different agglomeration index conditions is observed. This is shown in Figure 5(a). Under the condition of κτ = 0 and σ = 3.85, the relationship curve between “place-based” policy and aggregate output under different agglomeration index conditions represents “inverted U-shaped”, and the shape of the curve does not change fundamentally due to the change of aggregation index. With the increase of aggregation degree, the curve moves upward, indicating that the higher the aggregation degree, the more effective the implementation of the “place-based” policy. This is mainly due to economies of scale, that is, under the same input conditions, the higher the agglomeration index, the higher the total output.

Figure 5 Regional Policy Implementation and Aggregate Output Changes under Different Agglomeration Indices
Figure 5

Regional Policy Implementation and Aggregate Output Changes under Different Agglomeration Indices

Secondly, assuming that the basic conditions of regional development and the elasticity of product substitution remain unchanged, the impact of the implementation of “people-based” policies on total output under different agglomeration index conditions is observed. This is shown in Figure 5(b). Under the condition of κG = 0 and σ = 3.85, the relationship curve between the “people-based” policy and the total output shifts slightly upward with the increase of the degree of aggregation, indicating that the higher the degree of aggregation, the more effective the implementation of the “people-based” policy. However, “people-based” policies are less responsive to changes in the degree of aggregation than “place-based” policies.

Finally, assuming that the elasticity of product substitution remains unchanged, the impact of the implementation of “place-based” and “people-based” policies on the total output under the change of different agglomeration indices is observed. This is shown in Figure 5(c). The “place-based” and “people-based” policy mixes have “inverted U-shaped” relationship with aggregate output, which is similar to the relationship curve between “place-based” policies and aggregate output. However, the vertices of the curve shift to the left and the total output increases significantly. With the increase of the agglomeration index, the effect of policy mix on aggregate output is more obvious than that of using only one of them.

6 The Nature of the Debate On Regional Policy Paths

The nature of the debate on the path of regional policy lies in the different understandings of the role and the effect of government and market in regional economic development. The difference between China and the United States in the choice of “people-based” and “place-based” policy paths reflects the stark differences in regional policy practices between the two countries, and the fundamental difference is the difference in perception of the relationship between the government and the market.

As a developing socialist country, China always attach importance to the role of the government in promoting regional economic development. After the founding of New China, China implemented balanced development strategy that gave priority to heavy industry and took inland areas as the main spatial carrier, which directly promoted the development of basic industries in the central and western regions, and formed modern industrial system with relatively complete categories and relatively complete national economic system (Hao and Zhang, 2023). However, due to the low level of overall economic development and the relatively dispersed investment, overreliance on the role of the government and excessive pursuit of the balance of regional development aggravated the misallocation of resources among regions, which had led to the development dilemma of the national economy to a certain extent. Since the beginning of reform and opening up, taking economic construction as the central task had become the party’s basic line, and China had begun to implement unbalanced development strategy focusing on the coastal areas. On the one hand, it strengthened the tilt of government investment and preferential tax policies to the coastal areas, and on the other hand, it paid attention to deepening the reform of the economic system and mechanism, and used the market regulation mechanism to realize the free flow of various resources. Focusing on the phased goal of macroeconomic growth, China gave priority to the development of coastal areas by giving full play to the role of the government and the market at different levels, which in turn led to the rapid recovery and rapid development of the entire national economy. However, with the in-depth implementation of the regional unbalanced development strategy, the coastal areas continuously widened the development gap with the central and western regions by virtue of their own geographical advantages, relatively perfect market mechanisms and policy supporting advantages, and problems such as inter-regional conflicts of interests and local protectionism became increasingly prominent. In order to reverse this trend, China once again made major policy adjustment and began to implement coordinated regional development strategy that took into account efficiency and equity. In order to avoid the loss of macroeconomic efficiency caused by the excessive pursuit of balanced regional development, and to avoid the actual effect of excessive government investment being too dispersed, China adopted gradual regional support strategy according to the different development levels of each region. From 1999 to 2008, China successively put forward and implemented the strategy of developing the western region, the revitalization strategy of old industrial bases in the northeast region, the strategy of the rise of the central region and the strategy of taking the lead in the development of the eastern region. Focusing on the resource endowment and development status of different regions, the development gap between regions was gradually narrowed. Since the 18th National Congress of the Communist Party of China, major regional strategies such as the coordinated development of Beijing-Tianjin-Hebei, the development of the Yangtze River Economic Belt, and the construction of the Guangdong-Hong Kong-Macao Greater Bay Area have been steadily promoted, and the support policies for special regions such as the old revolutionary base areas have been further strengthened, and the space for the development of the marine economy has been further expanded, jointly building new pattern of regional coordinated development.

Due to the huge differences in social systems, history and culture, and development stages, the policy connotations of the “place-based” and “people-based” policies in the Chinese context are completely different from those in the United States. Although the regional policy of the United States also experience a period in which the government play a leading role. From the perspective of long-term development practice, especially since the 70s of the 20th century, the free market belief under the influence of neoliberal ideology has been dominant for a long time. The current shift of the United States’ regional policy to “people-based” fully demonstrates the return of its mainstream society’s belief in “market omnipotence”, so that it still restricts the role of government when the regional development gap widens again and the market mechanism is powerless. On the whole, China’s regional coordinated development strategy takes into account efficiency and fairness through the flexible use of “people-based” and “place-based” policies, and provides step-by-step and targeted support and guidance according to the development differences of different regions, deeply understands the negative externalities of the market and the limited role of the government, and neither worships the “big market” nor pursues the “big government”, but realizes the organic combination and benign positive interaction between the promising government and the effective market.

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Published Online: 2024-12-30

© 2024 Meng Nian, Haipeng Zhang, Yao Wang, Published by De Gruyter

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